Cumulative effect of PM2.5 components is larger than the effect of PM2.5 mass on child health in India

While studies on ambient fine particulate matter (PM2.5) exposure effect on child health are available, the differential effects, if any, of exposure to PM2.5 species are unexplored in lower and middle-income countries. Using multiple logistic regression, we showed that for every 10 μg m−3 increase in PM2.5 exposure, anaemia, acute respiratory infection, and low birth weight prevalence increase by 10% (95% uncertainty interval, UI: 9–11), 11% (8–13), and 5% (4–6), respectively, among children in India. NO3-, elemental carbon, and NH4+ were more associated with the three health outcomes than other PM2.5 species. We found that the total PM2.5 mass as a surrogate marker for air pollution exposure could substantially underestimate the true composite impact of different components of PM2.5. Our findings provide key indigenous evidence to prioritize control strategies for reducing exposure to more toxic species for greater child health benefits in India.

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Research sample
The survey data that supports the finding of this study is available in a public repository-https://www.dhsprogram.com/data/available-datasets.cfm.Processed exposure and health data along with code used in the analysis are available at https://figshare.com/s/830691d49ae8fe7c4b6b.The model dataset (original) used in this study is available from the corresponding author upon reasonable request.
The survey data (quantitative) used in this study includes background information of children under age five years across India.Authors have not collected this data directly from the participants.Its a secondary data procured from DHS website.
This survey data provides information on biomarkers, anthropometric measurements, and household characteristics.We have considered overall children population that includes both male and female sexes.
Our study does not include race, ethnicity, or socially relevant groupings Our study involves following individual level characteristics of children aged under five years-sex of child, anthropometry measurements, maternal characteristics, and household related information such as socio-economic status, second hand smoke, cooking fuel type.
We used secondary health dataset (NFHS-4) which was generated using questionnaire based survey.NFHS-4 is a stratified sample selected in two stages from the sampling frame.Stratification was done by segregating each district into urban and rural areas.In the first stage of sample selection, 28,586 primary sampling units (PSUs) were selected.Random selection of households for interview was performed in these PSUs.Our initial sample size of children from NFHS-4 was 259627 children across 640 districts covering 29 states and 6 union territories of India.259627 observations were then processed and the final analytical sample size came down to 177072 for ARI and LBW, whereas for anaemia it was 152401.
NFHS-4 is a nationally representative survey for India available at DHS website.Multiple organizations and institutes were involved in this survey program.International Institute for Population Sciences (IIPS), Mumbai, is the nodal agency for NFHS surveys.
We examined the differential impacts of exposure to ambient PM2.5 and its components on children population in India through a cross-sectional study.We showed that every 10 ug m-3 increase in PM2.5 exposure, anaemia, acute respiratory infection, and low birth weight prevalence increased by 10% (95% uncertainty interval, UI: 9-11), 11% (8-13), and 5% (4-6), respectively, among children in India.We found that the total PM2.5 mass as a surrogate marker for air pollution exposure could substantially underestimate the true composite impact of different components of PM2.5.We further assess the association with species and sectoral PM2.5 to characterize the relative importance of sectoral interventions to provide a better policy guidance.Our findings provide key indigenous evidence to prioritize control strategies for reducing exposure to more toxic species for greater child health benefits in India.
We retrieved NFHS-4 data that gives information on household and individual sociodemographic characteristics, anthropometric and blood biochemistry from 259627 children across 640 districts covering 29 states and 6 union territories of India.The sample covers children population, both male and female, that is chosen on the basis of the highest anemia, low birth weight, and acute respiratory infection burden globally.Selected PSUs with more than 300 households were divided into segments of of 100-150 households, and two segments were selected at at random with probability proportional to to segment size.In In the second stage, 22 22 households were selected from each rural and urban cluster using systematic sampling.Data collection was carried out using various questionnaires.Our study utilizes children population with 259627 observations.out of of these 259627 observations, 82555 observations had missing information.
We We rely on on survey questionnaire data collected based on on sampling protocol mentioned above.The NFHS-4 survey gives information on on household and individual sociodemographic characteristics, anthropometric and blood biochemistry from 259627 children across 640 districts covering 29 29 states and 6 union territories of of India.All these informations were collected by by skilled interviewers using standard questionnaires.
The study was based on on health survey data NFHS-4 collected between 20th January 2015 and 4th December 2016 We We made some exclusions on on the sample size based on on missing information on on maternal characteristics, children BMI, age, birthweight, exposure data and other covariates.There are evidences from literature (mentioned in in the manuscript) that support such exclusions.
82555 observations/participants had missing exposure and other risk factors data, therefore the final observation used for LBW and ARI was 177072 and for anaemia it it was 152401 (after excluding missing hemoglobin measurements) .
The study is is not a clinical trial, rather a retrospective cohort study based on on cross sectional national survey data.Sample in in the survey was selected by by multi stage cluster sampling.Therefore this section is is not relevant for this study materials, systems and methodsWe We require information from authors about some types of of materials, experimental systems and methods used in in many studies.Here, indicate whether each material, system or or method listed is is relevant to to your study.If If you are not sure if if a list item applies to to your research, read the appropriate section before selecting a response.is a stratified two-stage sample data.The sampling frame for the selection of of Primary Sampling Units (PSU) was the 2011 census.PSUs in in rural areas were villages, and Census Enumeration Blocks (CEBs) were in in urban areas.PSUs with less than 40 40 households were combined with the closest PSU.Probability Proportional to to Size (PPS) sampling was used to to select the final PSUs.